Spring Boot

Using Spring Cloud Functions with OpenShift Serverless

Using Spring Cloud Functions with OpenShift Serverless

Spring Cloud Functions are yet another interesting option for Java developers when building serverless applications. You have already seen how to build and run applications for Red Hat OpenShift Serverless using Quarkus, but in this article, we talk about how to use Spring Cloud Functions and walk you through those steps. These steps are similar to running any other Spring Boot application with OpenShift Serverless. One of the benefits of building an open hybrid serverless platform is giving developers a choice of programming languages, tools, frameworks, and portability across any environment to run serverless applications. Beyond that, you want to ensure that the developer experience and overall workflow is intuitive and practical, which is what you will learn here.

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Red Hat Runtimes brings Vert.x and Dekorate to Spring Boot 2.2.6

Red Hat Runtimes brings Vert.x and Dekorate to Spring Boot 2.2.6

The latest update to Red Hat Runtimes features support for Spring Boot 2.2.6, along with the Dekorate project and Spring Reactive. Together, these technologies are a boost for developers building Spring-based applications on the Red Hat OpenShift Container Platform. In this article, I present the highlights of this update.

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Adding keystores and truststores to microservices in Red Hat OpenShift

Adding keystores and truststores to microservices in Red Hat OpenShift

You might not need Secure Socket Layer (SSL)-based communication between microservices in the same cluster, but it’s often a requirement if you want to connect to a remote web service or message broker. In cases where you will expose a web service or other endpoints, you might also have to use a custom keystore in a microservice deployed on Red Hat OpenShift, so that external clients only connect with a specific truststore.

In this article, I show you how to configure a keystore and a truststore for a Java-based microservice built with Spring Boot. I used the Apache Camel and CXF libraries from Red Hat Fuse to develop the microservice. I used a source-to-image (S2I) deployment and tested the examples in Red Hat OpenShift 4.3.

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Change data capture with Debezium: A simple how-to, Part 1

Change data capture with Debezium: A simple how-to, Part 1

One question always comes up as organizations moving towards being cloud-native, twelve-factor, and stateless: How do you get an organization’s data to these new applications? There are many different patterns out there, but one pattern we will look at today is change data capture. This post is a simple how-to on how to build out a change data capture solution using Debezium within an OpenShift environment. Future posts will also add to this and add additional capabilities.

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Autoscaling Red Hat Fuse applications with OpenShift

Autoscaling Red Hat Fuse applications with OpenShift

In this article, we demonstrate Red Hat OpenShift’s horizontal autoscaling feature with Red Hat Fuse applications. The result is a Spring Boot-based application that uses the Apache Camel component twitter-search that searches Twitter for tweets based on specific keywords. If traffic or the number of tweets increases, and this application cannot serve all requests, then the application autoscales itself by increasing the number of pods. The ability to serve all requests is monitored by tracking this application’s CPU utilization on a particular pod. Also, as soon as traffic or CPU utilization is back to normal, the number of pods is reduced to the minimum configured value.

There are two types of scaling: horizontal and vertical. Horizontal scaling is where the number of application instances or containers is increased. Vertical scaling is where system resources like CPU and memory are increased at the running application’s or container’s runtime. Horizontal scaling can be used for stateless applications, whereas vertical scaling is more suitable for stateful applications.

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Autowire MicroProfile into Spring with Quarkus

Autowire MicroProfile into Spring with Quarkus

Eclipse MicroProfile and Spring Boot are often thought of as separate and distinct APIs when developing Java microservices. Developers default to their mental muscle memory by leveraging the APIs that they use on a daily basis. Learning new frameworks and runtimes can be a significant time investment. This article aims to ease the introduction to some popular MicroProfile APIs for Spring developers by enabling them to utilize the Spring APIs they already know while benefiting from significant new capabilities offered by Quarkus.

More specifically, this article covers the scope and details of the Spring APIs supported by Quarkus so Spring developers have a grasp of the foundation they can build on with MicroProfile APIs. The article then covers MicroProfile APIs that Spring developers will find helpful in the development of microservices. Only a subset of MicroProfile is covered.

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Extending support for Spring Boot 2.1.6 and Spring Reactive

Extending support for Spring Boot 2.1.6 and Spring Reactive

Red Hat Application Runtimes recently added extended support for the Spring Boot 2.1.6 runtime for Red Hat customers building Spring apps. Red Hat Application Runtimes provides application developers with a variety of application runtimes running on the Red Hat OpenShift Container Platform.

Introduction to Spring Boot

Spring Boot lets you create opinionated Spring-based standalone applications. The Spring Boot runtime also integrates with the OpenShift platform, allowing your services to externalize their configuration, implement health checks, provide resiliency and failover, and much more.

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